week3 YVR heat wave analysis
2024-05-20
Data
overview
## x y LOCAL_DATE TOTAL_PRECIPITATION
## Min. :-123.2 Min. :49.19 Length:31878 Min. : 0.000
## 1st Qu.:-123.2 1st Qu.:49.20 Class :character 1st Qu.: 0.000
## Median :-123.2 Median :49.20 Mode :character Median : 0.000
## Mean :-123.2 Mean :49.19 Mean : 3.098
## 3rd Qu.:-123.2 3rd Qu.:49.20 3rd Qu.: 3.400
## Max. :-123.2 Max. :49.20 Max. :91.600
## NA's :122
## MAX_TEMPERATURE MIN_TEMPERATURE TOTAL_RAIN MIN_REL_HUMIDITY
## Min. :-11.10 Min. :-17.800 Min. : 0.000 Min. : 11.00
## 1st Qu.: 8.90 1st Qu.: 2.600 1st Qu.: 0.000 1st Qu.: 55.00
## Median : 13.30 Median : 6.700 Median : 0.000 Median : 64.00
## Mean : 13.79 Mean : 6.445 Mean : 2.981 Mean : 64.62
## 3rd Qu.: 19.00 3rd Qu.: 11.100 3rd Qu.: 3.000 3rd Qu.: 75.00
## Max. : 34.40 Max. : 22.400 Max. :91.600 Max. :100.00
## NA's :50 NA's :41 NA's :81 NA's :14314## x y LOCAL_DATE TOTAL_PRECIPITATION
## 0 0 0 122
## MAX_TEMPERATURE MIN_TEMPERATURE TOTAL_RAIN MIN_REL_HUMIDITY
## 50 41 81 14314check wrangling data
check temp dist for in a random day from all year value
## [1] 10.6 8.3 11.7 10.6 12.2 10.0 10.6 12.2 12.2 12.8 13.9 11.1 10.0 10.6
## [15] 13.3 7.8 NA NA NA NA 10.6 8.9 7.2 7.8 8.9 9.4 12.2 12.8
## [29] 12.8 12.2 17.8 18.9 14.4 12.8 8.9 10.0 12.2 10.6 13.3 10.6 11.7 10.6
## [43] 9.4 11.1 10.6 11.7 12.8 12.8 15.6 16.1 12.2 12.8 13.9 12.2 15.0 12.8
## [57] 12.2 13.3 13.3 13.9 11.7 11.7 11.1 12.2 13.3 16.7 15.0 16.1 16.7 18.9
## [71] 16.1 12.8 13.3 8.9 12.2 10.6 7.2 8.3 6.7 8.9 11.1 11.1 15.0 12.8
## [85] 13.9 16.1 15.6 12.8 13.3 13.9 10.0 8.9 10.0 14.4 8.9 11.7 9.4 8.9
## [99] 12.8 7.2 11.1 13.3 11.7 11.7 11.1 7.8 10.0 8.9 8.3 8.9 8.9 10.6
## [113] 11.7 11.1 16.1 12.2 13.9 20.0 15.6 16.7 10.0 11.1 9.4 10.6 11.7 11.1
## [127] 11.7 11.1 11.1 8.3 10.0 11.1 10.6 11.7 8.9 12.2 11.7 8.3 12.8 7.8
## [141] 8.9 9.4 7.8 7.8 9.4 10.6 10.0 10.0 10.0 11.1 12.2 11.1 10.6 12.2
## [155] 10.0 11.1 12.2 18.3 13.3 11.1 12.2 11.7 10.6 9.4 11.1 8.3 5.6 11.7
## [169] 10.6 11.1 10.6 14.4 11.7 10.6 11.1 12.8 8.9 6.7 9.4 10.0 11.1 10.0
## [183] 12.8 11.7 10.0 11.1 9.4 10.0 4.4 8.9 12.2 7.8 12.2 14.4 16.1 11.1
## [197] 9.4 8.3 11.1 10.0 6.7 8.9 10.0 8.3 8.3 8.3 10.6 10.0 10.6 13.3
## [211] 10.0 7.2 8.9 11.7 8.9 12.8 11.1 12.2 11.1 10.0 10.0 11.7 13.3 15.0
## [225] 11.7 8.9 8.3 8.3 8.9 12.8 11.7 11.7 8.9 10.6 7.8 8.3 11.1 10.0
## [239] 7.2 12.8 8.9 10.6 11.7 11.1 10.0 12.2 10.0 10.0 10.6 10.6 8.9 8.9
## [253] 12.2 11.7 8.9 10.6 11.1 8.3 13.9 11.7 10.0 5.0 6.7 9.4 11.7 9.4
## [267] 11.1 8.3 12.8 12.2 8.9 8.9 4.4 3.9 6.1 9.4 10.6 8.3 12.2 7.8
## [281] 8.9 10.0 10.0 9.4 11.1 11.7 8.9 11.1 12.8 10.6 10.0 8.9 7.2 8.9
## [295] 10.0 10.0 11.7 10.0 8.9 8.9 10.6 11.1 7.8 11.7 10.6 10.0 10.6 11.1
## [309] 12.8 14.4 14.4 13.3 13.3 13.3 10.0 13.3 15.0 11.7 11.1 12.8 11.7 11.1
## [323] 13.9 15.6 11.7 15.0 13.3 12.8 13.9 13.9 11.7 7.2 8.9 11.7 10.6 12.8
## [337] 8.3 11.1 9.4 10.0 10.0 9.4 11.1 7.8 11.7 13.3 11.7 12.8 16.1 19.4
## [351] 11.7 12.8 10.0 12.2 10.6 9.4 11.1 13.3 17.2 17.2 10.6 12.2 13.9 13.9
## [365] 12.8 11.7 12.2 12.8 13.3 11.7 13.3 11.1 13.3 10.6 10.6 5.0 9.4 8.3
## [379] 8.9 10.6 11.1 8.9 10.0 12.8 15.6 13.9 12.8 10.6 11.7 11.7 16.1 10.6
## [393] 9.4 11.1 12.8 11.7 13.3 8.3 10.0 10.6 8.9 9.4 11.1 8.9 13.3 9.4
## [407] 9.4 6.7 7.8 11.1 11.1 10.6 11.1 14.4 18.3 11.1 11.7 10.6 12.8 10.6
## [421] 7.8 10.6 7.8 6.1 6.7 7.2 9.4 4.4 8.3 9.4 8.3 10.6 10.6 11.7
## [435] 11.1 10.0 8.9 11.1 11.1 12.8 15.6 13.3 16.1 15.6 16.1 13.3 13.3 10.6
## [449] 12.8 15.6 9.4 11.1 11.1 10.0 7.2 9.4 7.8 6.1 9.4 8.9 13.9 11.7
## [463] 12.8 13.3 10.6 13.9 15.0 11.7 11.1 10.6 8.3 10.0 10.0 10.0 8.9 8.9
## [477] 10.6 14.4 12.2 11.7 10.0 8.9 9.4 10.6 12.2 15.0 12.8 12.8 15.6 17.2
## [491] 9.4 10.0 6.1 8.9 10.6 10.0 10.0 12.8 10.6 10.0 12.2 8.9 11.1 11.7
## [505] 13.3 13.3 12.2 11.1 10.0 8.3 7.8 6.7 12.8 10.0 8.9 8.3 9.4 9.4
## [519] 12.8 9.4 11.1 11.1 12.2 10.0 13.3 10.6 10.0 9.4 7.8 6.7 6.1 7.2
## [533] 9.4 11.7 12.8 14.4 8.9 8.9 11.1 11.1 8.9 10.0 11.1 11.1 11.1 9.4
## [547] 10.0 11.1 8.9 11.1 9.4 10.0 12.8 13.9 15.0 8.9 10.0 10.6 12.8 10.0
## [561] 11.7 13.9 11.1 13.3 12.8 11.7 10.6 10.0 12.8 11.1 8.3 9.4 8.9 6.1
## [575] 8.3 7.2 8.3 10.6 11.1 8.9 8.9 9.4 7.8 7.2 9.4 8.3 8.9 7.2
## [589] 10.0 8.9 7.2 8.9 9.4 7.2 10.6 7.8 10.0 11.1 13.9 13.3 10.9 12.6
## [603] 10.5 11.0 9.4 8.6 10.0 9.5 10.0 9.8 12.0 11.1 11.7 12.4 13.1 11.6
## [617] 14.6 12.5 12.4 12.7 11.2 11.7 10.9 12.7 11.5 11.4 11.3 12.2 15.8 13.9
## [631] 12.8 14.3 13.9 12.1 10.5 12.3 11.4 13.0 11.3 10.7 10.0 9.3 10.4 9.6
## [645] 10.7 10.6 8.5 10.1 10.0 11.0 7.0 11.1 9.3 9.0 9.5 9.3 12.7 13.8
## [659] 16.7 15.2 15.5 13.5 11.2 14.6 15.4 12.8 12.2 10.3 9.4 8.4 10.1 9.8
## [673] 10.0 10.7 7.8 9.0 9.8 10.5 11.3 14.8 10.7 10.4 10.2 8.9 7.9 6.3
## [687] 9.8 12.2 7.1 10.0 10.2 13.9 13.0 10.7 13.5 13.0 11.9 8.3 10.8 11.2
## [701] 12.0 8.0 10.5 10.9 12.2 10.7 10.7 12.5 11.7 7.7 10.9 13.2 12.0 10.4
## [715] 11.8 13.2 12.4 13.2 12.2 11.1 8.5 10.5 10.4 6.9 6.1 7.9 8.2 10.3
## [729] 8.5 10.0 9.5 14.0 11.5 7.2 10.1 12.1 10.9 9.5 10.6 8.1 11.1 11.9
## [743] 11.0 10.9 11.2 9.4 11.1 13.1 12.5 11.5 10.9 13.9 11.7 12.5 10.1 10.4
## [757] 9.1 11.0 12.3 13.1 14.7 16.9 21.1 12.6 13.4 11.4 9.2 10.0 7.8 8.4
## [771] 8.5 10.2 7.4 9.6 10.8 10.7 10.2 10.1 10.9 10.8 11.2 9.5 9.5 9.9
## [785] 9.4 8.6 9.4 9.7 11.4 8.9 8.9 7.9 8.0 8.6 10.5 10.7 9.5 8.5
## [799] 9.9 10.7 10.9 12.6 13.4 12.5 12.9 13.5 12.8 14.3 12.4 13.0 8.5 9.1
## [813] 10.1 10.5 11.5 9.1 9.9 10.7 8.0 13.8 13.3 10.0 9.6 9.4 10.5 14.0
## [827] 13.9 13.3 12.4 13.1 15.1 9.8 10.7 14.4 16.6 14.2 14.7 22.1 14.0 10.4
## [841] 9.3 11.3 13.2 9.8 9.8 9.9 12.0 13.3 11.4 12.8 12.5 9.9 12.8 13.8
## [855] 12.0 7.6 7.1 8.0 10.1 11.0 13.6 15.7 15.4 17.5 14.4 13.6 13.8 13.7
## [869] 13.1 11.9 9.5 8.6 9.5 8.4 8.5 9.7 11.4 13.3 13.9 17.5 15.2 13.9
## [883] 11.9 16.1 13.4 13.0 10.8 10.0 10.8 8.6 9.5 13.5 11.9 9.5 10.0 12.1
## [897] 9.8 9.8 11.1 15.5 8.4 11.3 10.6 11.0 12.5 9.5 8.5 10.7 8.6 16.7
## [911] 10.7 9.7 11.2 10.7 9.8 12.5 15.7 11.9 13.1 12.8 9.7 8.8 9.4 10.6
## [925] 8.6 9.9 10.8 11.1 11.6 11.9 10.6 13.0 14.0 12.4 9.5 9.1 8.8 7.6
## [939] 8.9 8.7 9.5 10.3 9.2 10.1 8.8 10.9 13.4 10.8 10.1 11.7 12.3 12.0
## [953] 9.1 10.5 11.5 11.6 13.1 13.7 15.5 10.8 9.0 9.3 10.7 13.4 13.7 10.9
## [967] 7.3 8.3 7.7 11.3 12.6 8.9 10.6 10.9 12.8 5.1 8.2 10.5 11.0 14.0
## [981] 10.6 8.3 10.6 9.3 11.5 13.0 10.4 9.8 13.7 13.2 10.4 11.3 9.7 9.7
## [995] 12.9 11.5 11.2 10.9 11.7 11.4 11.3 9.5 10.6 10.2 8.7 13.6 16.3 13.8
## [1009] 11.3 9.9 9.6 13.4 13.1 18.5 14.9 10.6 11.2 12.8 17.6 12.6 9.6 12.0
## [1023] 11.2 12.0 12.0 11.7 11.1 11.5 10.0 12.6 8.4 10.9 8.3 10.9 11.9 10.2
## [1037] 10.4 15.9 12.8 9.8 8.5 10.9 11.2 13.4 13.8 13.1 8.2 16.4 10.9 12.4
## [1051] 6.0 7.5 9.8 10.9 11.8 11.4 9.9 11.3 12.9 13.7 9.2 10.3 8.0 10.0
## [1065] 9.1 9.0 11.2 9.8 10.1 8.8 9.1 7.3 5.0 7.4 8.3 8.0 7.2 9.6
## [1079] 11.3 7.9 7.8 9.1 6.9 11.1 8.5 9.7 10.2 6.9 9.8 7.7 9.5 5.7
## [1093] 8.6 9.3 11.0 12.9 12.6 12.7 12.3 9.8 13.8 14.9 13.4 9.6 10.1 10.6
## [1107] 9.9 9.4 9.4 13.8 8.0 11.0 11.3 12.4 9.6 13.6 12.4 11.5 10.6 13.6
## [1121] 13.5 9.8 10.9 9.1 6.0 8.8 8.6 8.8 10.2 11.1 9.5 14.3 11.2 9.5
## [1135] 9.1 6.4 10.9 13.6 10.4 8.9 8.4 7.6 9.5 9.4 11.2 11.7 13.1 14.1
## [1149] 13.5 13.8 15.7 15.3 13.8 13.5 12.7 8.7 5.3 8.4 10.7 11.8 12.4 11.1
## [1163] 10.2 11.6 12.1 10.7 12.3 13.2 10.4 13.2 12.9 11.8 11.4 13.0 11.1 18.8
## [1177] 16.9 14.3 10.4 17.2 12.9 11.2 12.5 10.9 11.8 13.2 14.6 9.6 10.1 10.5
## [1191] 11.6 11.1 11.6 12.7 15.0 17.1 17.7 15.6 14.8 14.5 11.7 12.5 12.3 10.8
## [1205] 10.9 9.9 12.1 8.9 13.5 11.8 11.7 10.8 10.6 10.3 13.8 11.6 8.9 8.4
## [1219] 8.3 9.4 8.2 13.3 9.8 8.4 13.2 10.9 9.1 9.9 9.1 9.0 16.7 17.3
## [1233] 13.4 10.6 11.4 13.0 12.3 14.3 14.2 13.7 13.9 14.9 15.8 14.6 13.7 11.0
## [1247] 10.7 10.1 8.4 9.4 9.0 8.7 10.2 13.4 9.5 10.5 8.8 9.1 8.8 9.9
## [1261] 6.7 9.8 9.1 8.2 10.2 10.7 9.7 10.1 9.7 9.5 10.5 13.1 11.9 11.3
## [1275] 10.3 8.4 12.7 12.3 9.8 12.5 12.6 12.1 11.2 15.1 12.1 10.6 9.4 12.0
## [1289] 9.2 9.7 11.5 12.3 9.8 9.0 7.7 9.2 10.5 16.7 12.7 NA 7.6 10.7
## [1303] NA 8.7 10.7 13.3 10.8 9.9 13.0 11.7 13.4 10.5 10.6 11.8 10.3 12.3
## [1317] 15.7 12.6 10.0 10.1## [1] 1320get 90th from the all year for all day value
## [1] 9.80 9.80 10.00 10.00 10.00 10.00 10.00 10.02 10.10 10.10 10.20 10.20
## [13] 10.30 10.33 10.23 10.40 10.40 10.40 10.40 10.50 10.52 10.50 10.60 10.60
## [25] 10.60 10.60 10.60 10.70 10.80 10.90 11.10 11.10 11.10 11.10 11.10 11.10
## [37] 11.10 11.10 11.10 11.10 11.10 11.10 11.10 11.10 11.10 11.10 11.10 11.10
## [49] 11.10 11.10 11.10 11.27 11.40 11.63 11.63 11.70 11.70 11.70 11.70 12.20
## [61] 11.70 11.74 11.80 12.20 12.20 12.20 12.50 12.50 12.60 12.60 12.80 12.80
## [73] 12.80 12.90 13.00 13.00 13.07 13.10 13.10 13.30 13.30 13.30 13.47 13.60
## [85] 13.70 13.78 13.90 13.90 13.90 14.00 14.40 14.40 14.60 14.80 14.90 15.00
## [97] 15.00 15.00 15.10 15.50 15.60 15.60 15.60 15.93 16.10 16.10 16.20 16.30
## [109] 16.60 16.70 16.80 17.10 17.20 17.43 17.80 17.80 17.80 18.00 18.10 18.30
## [121] 18.44 18.73 18.90 18.90 19.10 19.35 19.40 19.40 19.80 19.90 20.10 20.20
## [133] 20.40 20.40 20.60 20.80 20.91 21.10 21.10 21.10 21.40 21.50 21.70 21.70
## [145] 21.70 21.70 21.70 21.80 21.90 22.20 22.20 22.20 22.20 22.20 22.20 22.30
## [157] 22.20 22.20 22.20 22.40 22.48 22.70 22.80 22.80 22.80 22.80 22.80 22.80
## [169] 23.10 23.30 23.30 23.49 23.90 23.90 24.10 24.20 24.37 24.40 24.40 24.40
## [181] 24.40 24.50 24.57 24.70 24.80 25.00 25.00 25.00 25.00 25.00 25.00 25.00
## [193] 25.08 25.28 25.60 25.60 25.60 25.80 25.97 26.00 26.00 26.10 26.10 26.10
## [205] 26.31 26.20 26.16 26.10 26.10 26.10 26.10 26.10 26.10 26.10 26.10 26.10
## [217] 26.10 26.09 26.00 26.00 26.00 26.00 26.10 26.10 26.00 25.90 25.80 25.60
## [229] 25.60 25.30 25.20 25.00 25.00 25.00 24.90 24.70 24.50 24.40 24.38 24.20
## [241] 24.10 24.08 24.10 24.00 24.00 23.90 23.90 23.88 23.53 23.30 23.30 23.30
## [253] 23.30 23.20 22.80 22.80 22.57 22.20 22.20 22.20 21.90 21.70 21.70 21.70
## [265] 21.40 21.10 21.10 20.87 20.60 20.60 20.60 20.40 20.16 20.00 19.60 19.40
## [277] 19.26 18.90 18.60 18.30 18.30 18.20 17.80 17.80 17.57 17.30 17.20 17.20
## [289] 16.70 16.70 16.40 16.10 16.10 15.87 15.60 15.60 15.30 15.17 15.00 15.00
## [301] 15.00 14.90 14.70 14.50 14.40 14.40 14.20 14.00 13.90 13.90 13.80 13.68
## [313] 13.40 13.30 13.10 12.90 12.80 12.80 12.80 12.60 12.40 12.30 12.20 12.20
## [325] 11.80 11.70 11.70 11.70 11.50 11.30 11.40 11.20 11.10 11.10 11.00 10.90
## [337] 10.80 10.70 10.60 10.75 10.80 10.70 10.70 10.70 10.60 10.60 10.60 10.60
## [349] 10.60 10.60 10.60 10.56 10.40 10.16 10.00 10.00 10.00 10.00 10.00 10.00
## [361] 10.00 10.00 9.87 9.80 9.80 9.82Plot
plot given year temp dist vs baseline 90th
## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## `summarise()` has grouped output by 'Month'. You can override using the
## `.groups` argument.## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
plot all year temp in grey vs baseline
## Warning: Removed 301 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 300 rows containing missing values or values outside the scale range
## (`geom_line()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 301 rows containing missing values or values outside the scale range
## (`geom_line()`).
Analyze the hw
hw dist for certain 1 year
prepare for the data
## # A tibble: 32 × 7
## Month Day Percentile_90 MAX_TEMP_YEAR DayOfYear Condition Cumulative_Count
## <int> <int> <dbl> <dbl> <dbl> <lgl> <dbl>
## 1 1 4 10 10.4 4 TRUE 1
## 2 1 9 10.1 10.5 9 TRUE 1
## 3 1 10 10.1 11.1 10 TRUE 2
## 4 1 12 10.2 11.3 12 TRUE 1
## 5 3 18 13.1 14 77 TRUE 1
## 6 3 19 13.1 15.4 78 TRUE 2
## 7 3 20 13.3 13.7 79 TRUE 3
## 8 3 21 13.3 16.7 80 TRUE 4
## 9 3 22 13.3 17.3 81 TRUE 5
## 10 3 28 13.9 14.3 87 TRUE 1
## # ℹ 22 more rowsplot hw analysis for all year
plot overall count of hw through years
plot for heat map
examine specific year
## Warning: Removed 300 rows containing missing values or values outside the scale range
## (`geom_line()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 300 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 300 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 300 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 300 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).